Why the Global Warming Skeptics Are Wrong

Icebergs in Iceland’s Jökulsárlón lagoon, which is constantly growing as the Vatnajökull glacier—Europe’s largest—melts; photograph by Olaf Otto Becker from his book Under the Nordic Light: A Journey Through Time, Iceland, 1999–2011, which has just been published by Hatje Cantz

The threat of climate change is an increasingly important environmental issue for the globe. Because the economic questions involved have received relatively little attention, I have been writing a nontechnical book for people who would like to see how market-based approaches could be used to formulate policy on climate change. When I showed an early draft to colleagues, their response was that I had left out the arguments of skeptics about climate change, and I accordingly addressed this at length.

But one of the difficulties I found in examining the views of climate skeptics is that they are scattered widely in blogs, talks, and pamphlets. Then, I saw an opinion piece in The Wall Street Journal of January 27, 2012, by a group of sixteen scientists, entitled “No Need to Panic About Global Warming.” This is useful because it contains many of the standard criticisms in a succinct statement. The basic message of the article is that the globe is not warming, that dissident voices are being suppressed, and that delaying policies to slow climate change for fifty years will have no serious economic or environment consequences.

My response is primarily designed to correct their misleading description of my own research; but it also is directed more broadly at their attempt to discredit scientists and scientific research on climate change.1 I have identified six key issues that are raised in the article, and I provide commentary about their substance and accuracy. They are:

• Is the planet in fact warming?

• Are human influences an important contributor to warming?

• Is carbon dioxide a pollutant?

• Are we seeing a regime of fear for skeptical climate scientists?

• Are the views of mainstream climate scientists driven primarily by the desire for financial gain?

• Is it true that more carbon dioxide and additional warming will be beneficial?

As I will indicate below, on each of these questions, the sixteen scientists provide incorrect or misleading answers. At a time when we need to clarify public confusions about the science and economics of climate change, they have muddied the waters. I will describe their mistakes and explain the findings of current climate science and economics.

1.

The first claim is that the planet is not warming. More precisely, “Perhaps the most inconvenient fact is the lack of global warming for well over 10 years now.”

It is easy to get lost in the tiniest details here. Most people will benefit from stepping back and looking at the record of actual temperature measurements. The figure below shows data from 1880 to 2011 on global mean temperature averaged from three different sources.2 We do not need any complicated statistical analysis to see that temperatures are rising, and furthermore that they are higher in the last decade than they were in earlier decades.3

One of the reasons that drawing conclusions on temperature trends is tricky is that the historical temperature series is highly volatile, as can be seen in the figure. The presence of short-term volatility requires looking at long-term trends. A useful analogy is the stock market. Suppose an analyst says that because real stock prices have declined over the last decade (which is true), it follows that there is no upward trend. Here again, an examination of the long-term data would quickly show this to be incorrect. The last decade of temperature and stock market data is not representative of the longer-term trends.

The finding that global temperatures are rising over the last century-plus is one of the most robust findings of climate science and statistics.

2.

A second argument is that warming is smaller than predicted by the models:

The lack of warming for more than a decade—indeed, the smaller-than-predicted warming over the 22 years since the UN’s Intergovernmental Panel on Climate Change (IPCC) began issuing projections—suggests that computer models have greatly exaggerated how much warming additional CO2 can cause.

What is the evidence on the performance of climate models? Do they predict the historical trend accurately? Statisticians routinely address this kind of question. The standard approach is to perform an experiment in which (case 1) modelers put the changes in CO2 concentrations and other climate influences in a climate model and estimate the resulting temperature path, and then (case 2) modelers calculate what would happen in the counterfactual situation where the only changes were due to natural sources, for example, the sun and volcanoes, with no human-induced changes. They then compare the actual temperature increases of the model predictions for all sources (case 1) with the predictions for natural sources alone (case 2).

This experiment has been performed many times using climate models. A good example is the analysis described in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (for the actual figure, see the accompanying online material4). Several modelers ran both cases 1 and 2 described above—one including human-induced changes and one with only natural sources. This experiment showed that the projections of climate models are consistent with recorded temperature trends over recent decades only if human impacts are included. The divergent trend is especially pronounced after 1980. By 2005, calculations using natural sources alone underpredict the actual temperature increases by about 0.7 degrees Centigrade, while the calculations including human sources track the actual temperature trend very closely.

In reviewing the results, the IPCC report concluded: “No climate model using natural forcings [i.e., natural warming factors] alone has reproduced the observed global warming trend in the second half of the twentieth century.”5

3.

The sixteen scientists next attack the idea of CO2 as a pollutant. They write: “The fact is that CO2 is not a pollutant.” By this they presumably mean that CO2 is not by itself toxic to humans or other organisms within the range of concentrations that we are likely to encounter, and indeed higher CO2 concentrations may be beneficial.

However, this is not the meaning of pollution under US law or in standard economics. The US Clean Air Act defined an air pollutant as “any air pollution agent or combination of such agents, including any physical, chemical, biological, radioactive…substance or matter which is emitted into or otherwise enters the ambient air.” In a 2007 decision on this question, the Supreme Court ruled clearly on the question: “Carbon dioxide, methane, nitrous oxide, and hydrofluorocarbons are without a doubt ‘physical [and] chemical…substance[s] which [are] emitted into…the ambient air.’ …Greenhouse gases fit well within the Clean Air Act’s capacious definition of ‘air pollutant.’”6

In economics, a pollutant is a form of negative externality—that is, a byproduct of economic activity that causes damages to innocent bystanders. The question here is whether emissions of CO2 and other greenhouse gases will cause net damages, now and in the future. This question has been studied extensively. The most recent thorough survey by the leading scholar in this field, Richard Tol, finds a wide range of damages, particularly if warming is greater than 2 degrees Centigrade.7 Major areas of concern are sea-level rise, more intense hurricanes, losses of species and ecosystems, acidification of the oceans, as well as threats to the natural and cultural heritage of the planet.

In short, the contention that CO2 is not a pollutant is a rhetorical device and is not supported by US law or by economic theory or studies.

4.

The fourth contention by the sixteen scientists is that skeptical climate scientists are living under a reign of terror about their professional and personal livelihoods. They write:

Although the number of publicly dissenting scientists is growing, many young scientists furtively say that while they also have serious doubts about the global-warming message, they are afraid to speak up for fear of not being promoted—or worse….

This is not the way science is supposed to work, but we have seen it before—for example, in the frightening period when Trofim Lysenko hijacked biology in the Soviet Union. Soviet biologists who revealed that they believed in genes, which Lysenko maintained were a bourgeois fiction, were fired from their jobs. Many were sent to the gulag and some were condemned to death.

While we must always be attentive to a herd instinct, this lurid tale is misleading in the extreme. Some background on Lysenko will be useful. He was the leader of a group that rejected standard genetics and held that the acquired characteristics of an organism could be inherited by that organism’s descendants. He exploited the Soviet ideology about heredity, the need for agricultural production, and the favor of a powerful dictator—Stalin—to attract adherents to his theories. Under his influence, genetics was officially condemned as unscientific. Once he gained control of Russian biology, genetics research was prohibited, and thousands of geneticists were fired. Many leading geneticists were exiled to labor camps in Siberia, poisoned, or shot. His influence began to wane after Stalin’s death, but it took many years for Soviet biology to overcome the disastrous consequences of the Lysenko affair.8

The idea that skeptical climate scientists are being treated like Soviet geneticists in the Stalinist period has no basis in fact. There are no political or scientific dictators in the US. No climate scientist has been expelled from the US National Academy of Sciences. No skeptics have been arrested or banished to gulags or the modern equivalents of Siberia. Indeed, the dissenting authors are at the world’s greatest universities, including Princeton, MIT, Rockefeller, the University of Cambridge, and the University of Paris.

I can speak personally for the lively debate about climate change policy. There are controversies about many details of climate science and economics. While some claim that skeptics cannot get their papers published, working papers and the Internet are open to all. I believe the opposite of what the sixteen claim to be true: dissident voices and new theories are encouraged because they are critical to sharpening our analysis. The idea that climate science and economics are being suppressed by a modern Lysenkoism is pure fiction.

5.

A fifth argument is that mainstream climate scientists are benefiting from the clamor about climate change:

Why is there so much passion about global warming…? There are several reasons, but a good place to start is the old question “cui bono?” Or the modern update, “Follow the money.”

Alarmism over climate is of great benefit to many, providing government funding for academic research and a reason for government bureaucracies to grow. Alarmism also offers an excuse for governments to raise taxes, taxpayer-funded subsidies for businesses that understand how to work the political system, and a lure for big donations to charitable foundations promising to save the planet.

This argument is inaccurate as scientific history and unsupported by any evidence. There is a suggestion that standard theories about global warming have been put together by the scientific equivalent of Madison Avenue to raise funds from government agencies like the National Science Foundation (NSF). The fact is that the first precise calculations about the impact of increased CO2 concentrations on the earth’s surface temperature were made by Svante Arrhenius in 1896, more than five decades before the NSF was founded.

The skeptics’ account also misunderstands the incentives in academic research. IPCC authors are not paid. Scientists who serve on panels of the National Academy of Science do so without monetary compensation for their time and are subject to close scrutiny for conflicts of interest. Academic advancement occurs primarily from publication of original research and contributions to the advancement of knowledge, not from supporting “popular” views. Indeed, academics have often been subject to harsh political attacks when their views clashed with current political or religious teachings. This is the case in economics today, where Keynesian economists are attacked for their advocacy of “fiscal stimulus” to promote recovery from a deep recession; and in biology, where evolutionary biologists are attacked as atheists because they are steadfast in their findings that the earth is billions rather than thousands of years old.

In fact, the argument about the venality of the academy is largely a diversion. The big money in climate change involves firms, industries, and individuals who worry that their economic interests will be harmed by policies to slow climate change. The attacks on the science of global warming are reminiscent of the well-documented resistance by cigarette companies to scientific findings on the dangers of smoking. Beginning in 1953, the largest tobacco companies launched a public relations campaign to convince the public and the government that there was no sound scientific basis for the claim that cigarette smoking was dangerous. The most devious part of the campaign was the underwriting of researchers who would support the industry’s claim. The approach was aptly described by one tobacco company executive: “Doubt is our product since it is the best means of competing with the ‘body of fact’ that exists in the mind of the general public. It is also the means of establishing a controversy.”9

One of the worrisome features of the distortion of climate science is that the stakes are huge here—even larger than the economic stakes for keeping the cigarette industry alive. Tobacco sales in the United States today are under $100 billion. By contrast, expenditures on all energy goods and services are close to $1,000 billion. Restrictions on CO2 emissions large enough to bend downward the temperature curve from its current trajectory to a maximum of 2 or 3 degrees Centigrade would have large economic effects on many businesses. Scientists, citizens, and our leaders will need to be extremely vigilant to prevent pollution of the scientific process by the merchants of doubt.

6.

A final point concerns economic analysis. The sixteen scientists argue, citing my research, that economics does not support policies to slow climate change in the next half-century:

A recent study of a wide variety of policy options by Yale economist William Nordhaus showed that nearly the highest benefit-to-cost ratio is achieved for a policy that allows 50 more years of economic growth unimpeded by greenhouse gas controls. This would be especially beneficial to the less-developed parts of the world that would like to share some of the same advantages of material well-being, health and life expectancy that the fully developed parts of the world enjoy now. Many other policy responses would have a negative return on investment. And it is likely that more CO2 and the modest warming that may come with it will be an overall benefit to the planet.

On this point, I do not need to reconstruct how climate scientists made their projections, or review the persecution of Soviet geneticists. I did the research and wrote the book on which they base their statement. The skeptics’ summary is based on poor analysis and on an incorrect reading of the results.

The first problem is an elementary mistake in economic analysis. The authors cite the “benefit-to-cost ratio” to support their argument. Elementary cost-benefit and business economics teach that this is an incorrect criterion for selecting investments or policies. The appropriate criterion for decisions in this context is net benefits (that is, the difference between, and not the ratio of, benefits and costs).

This point can be seen in a simple example, which would apply in the case of investments to slow climate change. Suppose we were thinking about two policies. Policy A has a small investment in abatement of CO2 emissions. It costs relatively little (say $1 billion) but has substantial benefits (say $10 billion), for a net benefit of $9 billion. Now compare this with a very effective and larger investment, Policy B. This second investment costs more (say $10 billion) but has substantial benefits (say $50 billion), for a net benefit of $40 billion. B is preferable because it has higher net benefits ($40 billion for B as compared with $9 for A), but A has a higher benefit-cost ratio (a ratio of 10 for A as compared with 5 for B). This example shows why we should, in designing the most effective policies, look at benefits minus costs, not benefits divided by costs.

This leads to the second point, which is that the authors summarize my results incorrectly. My research shows that there are indeed substantial net benefits from acting now rather than waiting fifty years. A look at Table 5-1 in my study A Question of Balance (2008) shows that the cost of waiting fifty years to begin reducing CO2 emissions is $2.3 trillion in 2005 prices. If we bring that number to today’s economy and prices, the loss from waiting is $4.1 trillion. Wars have been started over smaller sums.10

My study is just one of many economic studies showing that economic efficiency would point to the need to reduce CO2 and other greenhouse gas emissions right now, and not to wait for a half-century. Waiting is not only economically costly, but will also make the transition much more costly when it eventually takes place. Current economic studies also suggest that the most efficient policy is to raise the cost of CO2 emissions substantially, either through cap-and-trade or carbon taxes, to provide appropriate incentives for businesses and households to move to low-carbon activities.

One might argue that there are many uncertainties here, and we should wait until the uncertainties are resolved. Yes, there are many uncertainties. That does not imply that action should be delayed. Indeed, my experience in studying this subject for many years is that we have discovered more puzzles and greater uncertainties as researchers dig deeper into the field. There are continuing major questions about the future of the great ice sheets of Greenland and West Antarctica; the thawing of vast deposits of frozen methane; changes in the circulation patterns of the North Atlantic; the potential for runaway warming; and the impacts of ocean carbonization and acidification. Moreover, our economic models have great difficulties incorporating these major geophysical changes and their impacts in a reliable manner. Policies implemented today serve as a hedge against unsuspected future dangers that suddenly emerge to threaten our economies or environment. So, if anything, the uncertainties would point to a more rather than less forceful policy—and one starting sooner rather than later—to slow climate change.

The group of sixteen scientists argues that we should avoid alarm about climate change. I am equally concerned by those who allege that we will incur economic catastrophes if we take steps to slow climate change. The claim that cap-and-trade legislation or carbon taxes would be ruinous or disastrous to our societies does not stand up to serious economic analysis. We need to approach the issues with a cool head and a warm heart. And with respect for sound logic and good science.

—February 22, 2012

1
The author is Sterling Professor of Economics at Yale University. He has received support for research on the economics of climate change during the last decade from the National Science Foundation, the Department of Energy, and the Glaser Foundation. Other than research associated with these and any future grants, the author declares no conflict of interest. ↩

2
The three series are produced by the UK Hadley Center, the US Goddard Institute for Space Studies ( GISS ), and the US National Climatic Data Center ( NCDC ). For those who question whether the series on global mean temperature are themselves products of a scientific conspiracy, here is yet a further check. Together with my colleague Xi Chen, I constructed yet another index of global mean temperature. We did this by getting grid-cell temperature data and aggregating these into a global average using land-area weights from our own research. To be even more conservative, we also did an audit of the grid-cell data by going back to station data selected quasi-randomly for selected grid cells around the world (such as Dakar, Albuquerque, Casablanca, Llasa, Yinchuan, and Yellowknife). The historical temperature series we constructed behaved very similarly to the ones constructed by the climate scientists. ↩

3
For those who would like a sample of how statisticians approach the issue of rising temperatures, here is an example. Many climate scientists believe that CO 2-induced warming has become particularly rapid since 1980. So we can use a statistical analysis to test whether the trend in global mean temperature is steeper in the 1980–2011 period than during the 1880–1980 period.

A regression analysis determines that the answer is yes, the rise in temperature is indeed faster. Such an analysis proceeds as follows: The series “ TAV t” is the average of the GISS, NCDC, and Hadley annual series. We estimate a regression of the form TAV t = α + β Yeart + γ (Year since 1980)t + εt. In this formulation, “Yeart” is simply the year, while (Year since 1980)t is 0 up to 1980 and then (Year-1980) for years after 1980. The Greek letters (α, β, and γ) are coefficients, while εt is a residual error. The estimated equation has a coefficient on Year of 0.0042 (t-statistic = 12.7) and a coefficient on (Year since 1980) of 0.0135 (t-statistic = 8.5). The interpretation is that temperatures in the 1880–1980 period were rising at 0.0042 °C per year, while in the later period they were rising at 0.0135 °C per year more rapidly. The t-statistic in parentheses indicates that the coefficient on (Year since 1980) was 8.5 times its standard error. Using standard tests for statistical significance, this large a t-coefficient would be obtained by chance less than one time in a million. We can use other years as break points, from 1930 to 2000, and the answer is the same: there has been a more rapid rise in global mean temperature in the most recent period than in earlier periods. ↩

4
I use this example to illustrate one experiment that has been conducted to determine the consistency of climate models and temperature observations. The experiment started with fourteen different climate models. The climate modelers calculated the temperature trajectory over the 1900–2005 period both with and without CO 2 and other human-induced factors. In the below figure from the IPCC Fourth Assessment Report, the bottom part shows the calculations including only natural forces, such as volcanic eruptions and changes in solar activity. The heavy black line is the actual temperature record, while the heavy blue line is the models’ average calculated global temperature with only natural forcings (“Without GHG s”). The several thin blue lines are the results of the individual models, while the gray vertical lines represent major cooling events due to volcanic eruptions.

The top part shows the calculations with both natural forces and with estimated greenhouse gas concentrations and forcings. Again, the heavy black line is the actual temperature record, while the heavy red line is the models’ average calculated global temperature with CO 2 and other greenhouse gases as well as natural forces (“With GHG s”). The cloud of thin yellow lines represents the results of the individual models

This experiment shows that the climate models are consistent with temperature trends over recent years only if the estimated warming induced by accumulations of CO 2 and other greenhouse gases are included. The source is Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change edited by S. Solomon and others (Cambridge University Press, 2007), p. 685f. ↩

8
A chilling account of the history is told in Valery N. Soyfer, “The Consequences of Political Dictatorship for Russian Science,” Nature Reviews Genetics, Vol. 2 (September 2001). ↩

9
Brown & Williamson Tobacco Corporation, “Smoking and Health Proposal” 1969, available at Legacy Tobacco Documents Library (legacy.library.ucsf.edu). There is an extensive literature on the tobacco industry’s strategy for distorting the scientific record and promoting views that were favorable to smoking. See Stanton Glantz et al., The Cigarette Papers (University of California Press, 1996); and Robert Proctor, Cancer Wars: How Politics Shapes What We Know and Don’t Know about Cancer (Basic Books, 1995). The history is updated to the modern era and industry attacks on environmental science in Naomi Oreskes and Erik Conway, Merchants of Doubt (Bloomsbury, 2010). ↩

10
The estimate is from A Question of Balance: Weighing the Options on Global Warming Policies (Yale University Press, 2008), p. 82. The updated number is calculated as follows. We update from 2005 to 2012 prices using the US GDP price index, which is estimated to be 15.6 percent higher in 2012 than in 2005. Then the number is put in 2012 economics by using a real discount rate of 6 percent per year. ↩

Letters

The author is Sterling Professor of Economics at Yale University. He has received support for research on the economics of climate change during the last decade from the National Science Foundation, the Department of Energy, and the Glaser Foundation. Other than research associated with these and any future grants, the author declares no conflict of interest. ↩

2

The three series are produced by the UK Hadley Center, the US Goddard Institute for Space Studies ( GISS ), and the US National Climatic Data Center ( NCDC ). For those who question whether the series on global mean temperature are themselves products of a scientific conspiracy, here is yet a further check. Together with my colleague Xi Chen, I constructed yet another index of global mean temperature. We did this by getting grid-cell temperature data and aggregating these into a global average using land-area weights from our own research. To be even more conservative, we also did an audit of the grid-cell data by going back to station data selected quasi-randomly for selected grid cells around the world (such as Dakar, Albuquerque, Casablanca, Llasa, Yinchuan, and Yellowknife). The historical temperature series we constructed behaved very similarly to the ones constructed by the climate scientists. ↩

3

For those who would like a sample of how statisticians approach the issue of rising temperatures, here is an example. Many climate scientists believe that CO 2-induced warming has become particularly rapid since 1980. So we can use a statistical analysis to test whether the trend in global mean temperature is steeper in the 1980–2011 period than during the 1880–1980 period.

A regression analysis determines that the answer is yes, the rise in temperature is indeed faster. Such an analysis proceeds as follows: The series “ TAV t” is the average of the GISS, NCDC, and Hadley annual series. We estimate a regression of the form TAV t = α + β Yeart + γ (Year since 1980)t + εt. In this formulation, “Yeart” is simply the year, while (Year since 1980)t is 0 up to 1980 and then (Year-1980) for years after 1980. The Greek letters (α, β, and γ) are coefficients, while εt is a residual error. The estimated equation has a coefficient on Year of 0.0042 (t-statistic = 12.7) and a coefficient on (Year since 1980) of 0.0135 (t-statistic = 8.5). The interpretation is that temperatures in the 1880–1980 period were rising at 0.0042 °C per year, while in the later period they were rising at 0.0135 °C per year more rapidly. The t-statistic in parentheses indicates that the coefficient on (Year since 1980) was 8.5 times its standard error. Using standard tests for statistical significance, this large a t-coefficient would be obtained by chance less than one time in a million. We can use other years as break points, from 1930 to 2000, and the answer is the same: there has been a more rapid rise in global mean temperature in the most recent period than in earlier periods. ↩

4

I use this example to illustrate one experiment that has been conducted to determine the consistency of climate models and temperature observations. The experiment started with fourteen different climate models. The climate modelers calculated the temperature trajectory over the 1900–2005 period both with and without CO 2 and other human-induced factors. In the below figure from the IPCC Fourth Assessment Report, the bottom part shows the calculations including only natural forces, such as volcanic eruptions and changes in solar activity. The heavy black line is the actual temperature record, while the heavy blue line is the models’ average calculated global temperature with only natural forcings (“Without GHG s”). The several thin blue lines are the results of the individual models, while the gray vertical lines represent major cooling events due to volcanic eruptions.

The top part shows the calculations with both natural forces and with estimated greenhouse gas concentrations and forcings. Again, the heavy black line is the actual temperature record, while the heavy red line is the models’ average calculated global temperature with CO 2 and other greenhouse gases as well as natural forces (“With GHG s”). The cloud of thin yellow lines represents the results of the individual models

This experiment shows that the climate models are consistent with temperature trends over recent years only if the estimated warming induced by accumulations of CO 2 and other greenhouse gases are included. The source is Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change edited by S. Solomon and others (Cambridge University Press, 2007), p. 685f. ↩

A chilling account of the history is told in Valery N. Soyfer, “The Consequences of Political Dictatorship for Russian Science,” Nature Reviews Genetics, Vol. 2 (September 2001). ↩

9

Brown & Williamson Tobacco Corporation, “Smoking and Health Proposal” 1969, available at Legacy Tobacco Documents Library (legacy.library.ucsf.edu). There is an extensive literature on the tobacco industry’s strategy for distorting the scientific record and promoting views that were favorable to smoking. See Stanton Glantz et al., The Cigarette Papers (University of California Press, 1996); and Robert Proctor, Cancer Wars: How Politics Shapes What We Know and Don’t Know about Cancer (Basic Books, 1995). The history is updated to the modern era and industry attacks on environmental science in Naomi Oreskes and Erik Conway, Merchants of Doubt (Bloomsbury, 2010). ↩

10

The estimate is from A Question of Balance: Weighing the Options on Global Warming Policies (Yale University Press, 2008), p. 82. The updated number is calculated as follows. We update from 2005 to 2012 prices using the US GDP price index, which is estimated to be 15.6 percent higher in 2012 than in 2005. Then the number is put in 2012 economics by using a real discount rate of 6 percent per year. ↩